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DBMS > Databricks vs. MySQL vs. Oracle Berkeley DB

System Properties Comparison Databricks vs. MySQL vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMySQL  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Widely used open source RDBMSWidely used in-process key-value store
Primary database modelDocument store
Relational DBMS
Relational DBMS infoKey/Value like access via memcached APIKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.86
Rank#19  Overall
#3  Document stores
#13  Relational DBMS
Score1182.79
Rank#2  Overall
#2  Relational DBMS
Score3.38
Rank#101  Overall
#19  Key-value stores
#3  Native XML DBMS
Websitedatabricks.comwww.mysql.comwww.oracle.com/­technetwork/­database/­database-technologies/­berkeleydb/­overview/­index.html
Technical documentationdatabricks.com/­documentationdev.mysql.com/­docdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperDatabricksOracle infosince 2010, originally MySQL AB, then SunOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release201319951994
Current release8.0.32, January 202318.1.40, May 2020
License infoCommercial or Open SourceOpen SourceOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • PlanetScale: Deploy a fully managed database with the reliability of MySQL and the scale of open source Vitess with PlanetScale today. Predictably scale, increase workflow velocity, and deploy features with zero downtime.
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Implementation languageC and C++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedFreeBSD
Linux
OS X
Solaris
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesPython
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoproprietary syntaxno
Triggersyesyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning, sharding with MySQL Cluster or MySQL Fabricnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infonot for MyISAM storage engineACID
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept infono user groups or rolesno

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